How to convert pandas column to numeric if there are strings?

I have a dataset that has numerical values, empty values and text values. I want to do the following in pandas:

1. Numerical Values -> Float
2. Empty Values -> N/A
3. Text Values -> N/A

When I try to run astype('float'), I get an error:

import pandas as pd
data = ['5', '4', '3', '', 'NO DATA ', '5']
data = ['5', '4', '3', '', '', '5']
df = pd.DataFrame({'data': data})
df[['data']].astype('float')

I've tried to look over the documentation and stackoverflow, but I didn't find out how to do this.

Using panda's to_numeric function, we can turn any valid value into floats, while turning invalid values into NaNs:

import pandas as pd
data = ['5', '4', '3', 'NO DATA', '', '5']
df = pd.DataFrame({'data': data})
df['data'] = pd.to_numeric(df['data'], errors='coerce')

The errors='coerce' makes sure that invalid values are turned into NaN instead of raising an error.

And the result will be:

data
0	5.0
1	4.0
2	3.0
3	NaN
4	NaN
5	5.0